Locating a radio device such as a user equipment (UE) is important inter alia for emergency services, cargo tracking, theft protection as well as services using the location as a service parameter or context dependency, such as search engines, speech recognition and augmented reality. Furthermore, some jurisdictions require mobile operators to locate emergency callers. Such services are collectively referred to as location-based services (LBS).
Since reliability and locating accuracy determine rescue success, it is desirable to seamlessly integrate the locating technique into radio access networks (RANs). In existing cellular RANs implementing the Universal Mobile Telecommunications System (UMTS) or Long Term Evolution (LTE) according to the Third Generation Partnership Project (3GPP), two or more transmission and reception points (TRPs) such as base stations are within range of radio communication relative to the radio device.
However, a conventional technique for locating the radio device is based on distance estimates, which is suboptimal in some respects. Firstly, the conventional locating technique is very susceptible to errors in the estimated distance between the radio device and the respective TRP. Secondly, the radio device has to perform additional procedures, such as a random access (RA) procedure towards multiple TRPs for estimating a timing advance (TA) or measuring and reporting of positioning reference signals (PRSs), causing an overhead over baseline active mode signaling and radio device operation. For example, the distances are estimated based on the time difference of arrival (TDOA) in RANs using Wideband Code Division Multiple Access (WCDMA). The TDOA of signals from multiple TRPs is analyzed by the radio device and the TDOA is reported to the RAN, as described in the book “UMTS networks: Architecture, mobility and services”, Wiley, 2005, 2nd ed., p. 231. In LTE, the radio device measures and reports the TDOA of PRSs.
An alternative conventional locating technique estimates angles for geographical position estimation in order to not rely on accurate distance estimates. For example, the radio device estimates an angle of arrival (AOA) of signals from multiple TRPs (loc. cit., p. 232). The document “SpotFi: Decimeter Level Localization Using WiFi” by M. Kotaru, K. Joshi, D. Bharadia and S. Katti, Proceedings of the SIGCOMM 2015, ACM Conference on Special Interest Group on Data Communication, pp. 269-282, describes an implementation of “SpotFi”, which is an indoor localization system deployable on commodity Wi-Fi infrastructure without hardware or firmware changes as an example of a non-cellular RAN. “SpotFi” incorporates algorithms that compute the AoA of multipath components at a Wi-Fi access point (AP) as an example for a TRP. In order to detect multipath propagation, the AoA of the direct path between the radio device and the TRP is identified at the TRP by receiving multiple subcarriers.
However, conventional techniques such as SpotFi require the radio device to transmit signals to a plurality of TRPs, and each of the TRPs is required to receive the signals and estimate the AoA based on the received signals over multiple subcarriers. Hence, the conventional techniques occupy radio resources of the RAN in space and frequency at a plurality of TRPs for locating a single radio device.